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Overcoming Matrix Multiplication Bottlenecks in Transformer Training

The current methods for transformer training are hindered by the limitations of matrix multiplication, which can be a significant bottleneck. This bottleneck can lead to increased computational costs and reduced efficiency in training large models. The issue seems to be related to the mathematical objects used to represent information in transformers.

Computing & Technology, Computer Science, Machine Learning